We investigated whether the increased prevalence of gentamicin resistance in Salmonella from human infections was related to a similar increased prevalence in isolates from broiler chickens and whether this increase may have been due to coselection from use of lincomycin-spectinomycin in chickens on farms. Whole-genome sequencing was performed on gentamicin-resistant (Genr) Salmonella isolates from human and chicken sources collected from 2014 to 2017 by the Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS). We determined the genomic relatedness of strains and characterized resistance genes and plasmids. From 2014 to 2017, 247 isolates of Genr Salmonella were identified by CIPARS: 188 were from humans, and 59 were from chicken sources (26 from live animals on farm and 33 from retail meat). The five most common Genr serovars were Salmonella enterica serovars Heidelberg (n = 93; 31.5%), 4,[5],12:i:− (n = 42; 14.2%), Kentucky (n = 37; 12.5%), Infantis (n = 33; 11.2%), and Typhimurium (n = 23; 7.8%). Phylogenomic analysis revealed that for S. Heidelberg and S. Infantis, there were closely related isolates from human and chicken sources. In both sources, resistance to gentamicin and spectinomycin was most frequently conferred by aac(3)-VIa and ant(3′′)-Ia, respectively. Plasmid closure confirmed linkages of gentamicin and spectinomycin resistance genes and revealed instances of similar plasmids from both sources. Gentamicin and spectinomycin resistance genes were linked on the same plasmids, and some plasmids and isolates from humans and chickens were genetically similar, suggesting that the use of lincomycin-spectinomycin in chickens may be selecting for gentamicin-resistant Salmonella in broiler chickens and that these resistant strains may be acquired by humans.


In Canada, there are an estimated 4.0 million cases of domestically acquired foodborne illness annually, affecting approximately one out of eight Canadians (1). Nontyphoidal Salmonella (NTS) is estimated to be the fourth most common cause of foodborne illness in Canada, with approximately 270 cases per 100,000 population, annually (1). NTS usually causes acute gastroenteritis illness, which presents as diarrhea, vomiting, nausea, and abdominal cramps (2, 3). Invasive infections can develop in up to 6% of NTS cases where infants, the elderly, and immunocompromised individuals are more prone to invasive infections (2, 4). Bacterial gastroenteritis is usually self-limiting; however, antimicrobials may be prescribed for higher-risk individuals and patients with invasive infections. When treatment is indicated, most Canadian clinical treatment guidelines recommend the use of either a fluoroquinolone (such as ciprofloxacin) or azithromycin, however, ceftriaxone or trimethoprim-sulfamethoxazole may also be prescribed (5).
Gentamicin is a broad-spectrum bactericidal aminoglycoside that inhibits protein synthesis (68). The Health Canada Veterinary Drugs Directorate categorizes gentamicin as a category II antimicrobial (highly important to human medicine) (9). It is sometimes used to treat certain types of invasive/systemic infections caused by Enterobacterales other than Salmonella (10, 11), and the World Health Organization recommends gentamicin and ampicillin combination therapy for neonatal sepsis in low- and middle-income countries (12). Aminoglycoside-modifying enzymes (AMEs) are the most common mechanism of gentamicin resistance (Genr) and include the N-acetyltransferases (AACs), O-nucleotidyltransferases (ANTs), and O-phosphotransferases (APHs). Each of these classes contain numerous subclasses of enzymes that modify gentamicin and other medically relevant aminoglycosides at different positions (13). These resistance genes can be carried on mobile genetic elements that facilitate transfer between bacteria and promote dissemination within bacterial populations (14).
In recent years, antimicrobial use and antimicrobial resistance (AMR) within production animals have been a public health focus, with concern about the potential transfer of resistance genes or resistant organisms from animals to humans via the food chain. In 2016, approximately 80% of antimicrobials sold in Canada were for use in production animals, mostly for disease prevention (15). In response to increasing levels of third-generation cephalosporin resistance in broiler chickens and chicken meat, Chicken Farmers of Canada implemented an industry-wide ban in 2014 on the preventative use of category I antimicrobials (very high importance to human medicine), which included ceftiofur and other third/fourth-generation cephalosporins (15). By the end of 2018, preventive use of category II antimicrobials (high importance to human medicine, including gentamicin, lincomycin, and spectinomycin [15]) was also banned by the industry. Following the ban on ceftiofur, the Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS) observed an increasing prevalence of Genr in Salmonella enterica isolates from both human infections and broiler chicken sources. It was hypothesized that the increased use of the combination of lincomycin-spectinomycin on chicken farms may be coselecting for Genr (16, 17). Chalmers et al. described the linkage of Genr and spectinomycin resistance (Specr) genes on the same plasmid in Escherichia coli isolates from broiler chicken in Quebec, Canada, in 2017 (17).
In this report, we carried out a genomic study of Genr Salmonella from human and chicken sources. We compared the genetic backgrounds, resistance genes, and resistance plasmids between human and chicken sources. We also investigated whether there was plasmid linkage of Genr and Specr genes in Salmonella.


From 2003 to 2017, CIPARS collected antimicrobial susceptibility data for 46,837 human Salmonella isolates and 15,602 chicken Salmonella isolates, and from 2014 to 2017 identified 247 isolates of Genr Salmonella from human and chicken sources (188 human, 59 chicken). For human-source Salmonella collected from 2014 to 2017, routine antimicrobial susceptibility testing (AST) was carried out on five NTS serovars as well as other select serovars (due to concerns regarding antimicrobial resistance), and the proportion of Genr isolates in each serovar was as follows: Salmonella enterica serovars Heidelberg (n = 66; 35.1%), 4,[5],12:i:− (n = 41; 21.8%), Kentucky (n = 25; 13.3%), Infantis (n = 21; 11.2%), Typhimurium (n = 16; 8.5%), Newport (n = 11; 5.9%), Enteritidis (n = 5; 2.7%), and Dublin (n = 3; 1.6%). The Genr Salmonella proportions among these eight serovars for chicken-source isolates were as follows: Heidelberg (n = 27; 45.8%), Infantis (n = 12; 20.3%), Kentucky (n = 12; 20.3%), Typhimurium (n = 7; 11.9%), and 4,[5],12:i:− (n = 1; 1.7%). Comparing the proportions of these eight serovars that demonstrated Genr in the time periods of 2003 to 2013 and 2014 to 2017, Genr prevalence rose significantly from 1.3% (n = 316 of 23,813) to 2.0% (n = 188 of 9,467) in humans (P value <0.05) and from 1.2% (n = 47 of 3,927) to 2.1% (n = 33 of 1,542) in retail meat (P value of <0.05). Prevalence did not change significantly in animals, going from 1.0% (n = 51 of 5,016) in 2003 to 2013 to 1.3% (n = 26 of 1,968) in 2014 to 2017 (P value of 0.31) (Fig. 1).
FIG 1 Percent of Salmonella isolates resistant to gentamicin from humans and chickens (animal and retail) collected from 2003 to 2017. Shown are the combined gentamicin resistance (Gen-R) prevalence estimates of the eight serovars for which CIPARS carried out antimicrobial susceptibility testing on human isolates (Salmonella 4,[5],12:i:−, Dublin, Enteritidis, Heidelberg, Infantis, Kentucky, Newport, and Typhimurium). From 2003 to 2017, Genr isolates from the following sources were collected and tested: 504 from 33,280 human isolates (filled squares), 77 from 6,948 chicken (animal) isolates (open circles), and 80 from 5,469 chicken (retail) isolates (filled circles).
Phylogenomic analysis was carried out on the five serovars that displayed the highest proportions of gentamicin resistance (S. enterica serovars Heidelberg, Infantis, 4,[5],12:i:−, Typhimurium, and Kentucky). There were three clusters of closely related isolates of S. Heidelberg from human and chicken sources suggesting potential transmission between chicken and humans (Fig. 2A). One cluster contained two chicken (animal) isolates and four human isolates that were isolated from the same year and province with the same Genr genes, but different Specr genes. The second and third clusters of S. Heidelberg each had three instances of human- and chicken-source isolates found to be collected from the same year and province, and in these cases, these isolates differed by 6 to 12 single nucleotide variants (SNVs) in the second cluster and 1 to 5 SNVs in the third cluster. Most of these isolates also had the same Genr and Specr genes. Analysis of the S. Infantis isolates (Fig. 2B) revealed three clusters containing isolates from all three sources (human, chicken animal, and retail meat) that differed by fewer than 10 SNVs. For two clusters, one human isolate and one retail isolate were collected from the same provinces in the same years; one of these pairs differed by six SNVs and contained the same Genr and Specr genes, suggesting potential transmission. For the 4,[5],12:i:− and Typhimurium trees, one isolate each was excluded due to having large genetic distances from the other isolates, which skewed the trees and reduced the resolution of the rest of the isolates. One isolate of S. 4,[5],12:i:− from chicken differed from two human isolates by only four SNVs; the isolates were from the same year but from different provinces (Fig. 2C). One cluster of S. Typhimurium contained one isolate each from human source and retail chicken; however, isolates were from different years and provinces (Fig. 2D). Human and chicken isolates of S. Kentucky were genetically distinct and differed by approximately 20,000 SNVs (Fig. 2E). Within each source, S. Kentucky isolates differed by 2 to 36 SNVs (human source) and 2 to 110 SNVs (chicken source).
FIG 2 Phylogenomic relationships of Genr Salmonella isolates from humans, live and recently slaughtered chicken (animal), and chicken at retail. Phylogenomic analyses based on maxiumum likelihood phylogeny was carried out with the SNVPhyl pipeline for the five most common Genr serovars. The reference genomes used and number of isolates for each serovar were NZ_CP012924.1 for S. Heidelberg (n = 93) (A), internal reference (15-6881) for S. Infantis (n = 33) (B), NZ_CP038849.1, for S. 4,[5],12:i:− (n = 42) (C), NZ_CP038434.1 for S. Typhimurium (n = 22) (D), and NZ_CP026327.1 for S. Kentucky (n = 37) (E). Squares represent human (red), chicken-animal (green), and chicken-retail (blue) sources. SNV variation between isolates in potential clusters is indicated. The percentage of the reference genome that was in the core genome upon which the trees are based ranged from 84.69% to 91.39%.
Among 247 Genr Salmonella from human and chicken sources, coresistance was observed most commonly with sulfisoxazole (n = 232; 93.9%) and streptomycin (n = 205; 83.0%). In addition, coresistance was also observed with tetracycline (n = 164; 66.4%), ampicillin (n = 131; 53.0%), chloramphenicol (n = 61; 24.7%), nalidixic acid (n = 50; 20.2%), ceftriaxone (n = 49; 19.8%), amoxicillin-clavulanic acid (n = 42; 17.0%), trimethoprim-sulfamethoxazole (n = 42; 17.0%), cefoxitin (n = 41; 16.6%), ciprofloxacin (n = 36; 14.6%), and azithromycin (n = 9; 3.6%). Alleles of the extended-spectrum β-lactamase (ESBL) gene blaCTX-M was detected in 6.4% of human isolates and in no chicken isolates, while blaCMY-2 was detected in 12.8% of human isolates and 28.8% of chicken isolates. The mobile colistin resistance genes mcr-1 and mcr-3.2 were each detected once in S. 4,[5],12:i:− isolates from humans. The proportion of multiclass resistance differed between human and chicken samples with a greater proportion of human isolates showing multiclass resistance (Fig. 3). Resistance to three classes was observed in 10.1% of Genr human isolates and in 44.1% of agrifood isolates. Resistance to four or five classes was observed in 53.2% of human isolates but only 20.3% of agrifood isolates. Resistance to six or seven classes was observed in 9.0% of human isolates but in no chicken isolates. Human-source isolates were significantly more likely to be resistant to four to seven antimicrobial classes than chicken-source isolates (P value of 0.000001). The human-source isolates with resistance to six and seven classes were S. 4,[5],12:i:− (n = 9), Infantis (n = 4), Typhimurium (n = 3), and Newport (n = 1).
FIG 3 The number of antimicrobial classes to which Genr Salmonella from human and chicken isolates are resistant. CIPARS tested antimicrobials belonging to seven classes: aminoglycosides, β-lactams, folate pathway inhibitors, macrolides, phenicols, quinolones, and tetracyclines. Human isolates are represented as black bars, chicken-animal isolates are represented as gray bars, and chicken-retail isolates are represented as white bars.
All Genr genes found in human and chicken (animal and retail) isolates are shown in Table 1. The Genr genes found in human isolates were aac(3)-VIa (45.4%; n = 88), aac(3)-IId (23.7%; n = 46), aac(3)-Id (12.9%; n = 25), aac(3)-IVa (5.7%; n = 11), aac(3)-IIa (4.1%; n = 8), ant(2′′)-Ia (2.6%; n = 5), and aac(6)-Ib-cr (1.5%; n = 3), with no known Genr gene detected in 3.6% (n = 7) of isolates. Additionally, we detected one 16S rRNA methyltransferase, rmtB. In chicken isolates, the Genr genes were aac(3)-VIa (85.2%; n = 52), aac(3)-IId (6.6%; n = 4), ant(2′′)-Ia (3.3%; n = 2), aac(6)-Ib3 (3.3%; n = 2), and aac(3)-IVa (1.6%; n = 1). Of lincomycin and spectinomycin resistance (Lincor/Specr) genes detected, most conferred resistance to spectinomycin alone. The Specr genes in human-source isolates were ant(3′′’)-Ia (39.0%; n = 83), followed by aadA2 (12.7%; n = 27), aadA7 (11.7%; n = 25), aadA1 (8.0%;n = 17), aadA17 (2.8%; n = 6), aadA5 (0.9%; n = 2), and aadA22 (0.5%; n = 1), with none detected in 21.1% (n = 45). Lincor was conferred by lnu(F) (3.3%; n = 7) in human isolates. The following Specr genes were found in chicken isolates: ant(3′′)-Ia (76.3%; n = 45), aadA2 (6.8%; n = 4), and aadA1 (5.1%; n = 3), while no genes were detected in 11.9% (n = 7). No Lincor genes were found in chicken isolates. Genr and Lincor/Specr genes were frequently found on the same contig, most often aac(3)-VIa (Genr) and ant(3′′)-Ia (Specr), where aac(3)-VIa was found in 96.0% of isolates carrying ant(3′′)-Ia, and vice versa, ant(3′′)-Ia was found in 87.6% of isolates carrying aac(3)-VIa.
TABLE 1 Genes conferring gentamicin resistance in Salmonella from human and chicken sources
Genr gene No. of genes conferring Genr to serovarSubtotal no.
of genes
Total no.
of genes
(n = 93)
(n = 42)
(n = 37)
(n = 33)
(n = 23)
(n = 19)
aac(3)-VIaHuman5617 122188 
Chicken - animal11 84  23140
Chicken - retail14 357 29 
Chicken - animal   1  150
Chicken - retail1  2  3 
aac(3)-IdHuman  25   25 
Chicken - animal      025
Chicken - retail      0 
aac(3)-IVaHuman 5 33 11 
Chicken - animal  1   112
Chicken - retail      0 
aac(3)-IIaHuman     88 
Chicken - animal      08
Chicken - retail      0 
ant(2′')-IaHuman1  1 35 
Chicken - animal 1    17
Chicken - retail1     1 
aac(6′)-Ib-crHuman 2  1 3 
Chicken - animal      03
Chicken - retail      0 
aac(6′)-Ib3Human      0 
Chicken - animal2     22
Chicken - retail      0 
rmtBHuman     11 
Chicken - animal      01
Chicken - retail      0 
NoneHuman12 1 37 
Chicken - animal      07
Chicken - retail      0 
Total no. 984438332418  
Of 247 phenotypically Genr isolates, 94 (38.1%) possessed Genr genes that were located on contigs with known incompatibility (Inc) groups. Of those 94, the majority were located on IncI1 plasmids (85.1%; n = 80) with the remainder on IncA/C2 (11.7%; n = 11) and other plasmids (3.2%; n = 3). Of 247 isolates, 93 (37.7%) had Lincor/Specr genes on contigs with known Inc groups, with the majority located on IncI1 plasmids (84.9%; n = 79) and the remainder on IncA/C2 (10.8%; n = 10) and other plasmids (4.3%; n = 4).
Long-read sequencing was performed on 25 human isolates and four chicken isolates. Serovars included were S. 4,[5],12:i:− (n = 9), Infantis (n = 7), Typhimurium (n = 6), Heidelberg (n = 3), Kentucky (n = 3), and Newport (n = 1). Genr plasmids in these isolates were analyzed, and most also possessed Specr genes. Seven plasmids were IncHI2 (all human), five were IncA/C2 (four human, one animal), five were IncI1 (three human, two animal), eight were various other Inc types (including IncF, IncL/M, and IncQ1 [animal isolate]), and three had no identified Inc type (all human), while one isolate (human) had no plasmids (all resistance genes on chromosome). Plasmids of the same Inc type were aligned with the Gview server using the pangenome feature (Fig. 4A to E). Plasmids within each of the groups (IncA/C2, IncHI2, IncI1, and no Inc) showed diversity in length and content. For the longest homologous region between any pair of plasmids within each of the four major Inc groups, there was a minimum of 99.70%, 98.45%, 98.41%, and 100.00% nucleotide identity, respectively. The group named “other,” containing plasmids belonging to various Inc types, showed a much wider range of sequence similarity (82.88% to 100%). The four plasmids from chicken isolates (one IncA/C2, two IncI1, and one from “other” Inc group) were each compared to their most similar human-source counterparts from the same Inc group. Within the IncA/C2 group, there was >99.9% sequence similarity between the human-source plasmid (light green) and the chicken-source plasmid (red), for the entire length of the plasmid (Fig. 4A). Both plasmids were from S. Infantis isolates. For IncI1, a human-source plasmid (orange) had 99.6% and 99.2% nucleotide identity over 84.9% and 87.6% of the length of two plasmids from chicken, shown in red and brown, respectively (Fig. 4C). For the “other” Inc group, there was >99.9% sequence similarity between a human-source plasmid from S. Heidelberg (purple) and a chicken-source plasmid from Heidelberg (red), over 98.7% of the plasmid (Fig. 4D).
FIG 4 Pangenome sequence alignments of closed plasmids obtained through long-read sequencing. Genr plasmids of similar incompatibility (Inc) groups were aligned in Gview, which displays a pangenome at the bottom of each alignment containing all of the genetic content of all plasmids. Genetic maps are shown for IncA/C2 (A), IncHI2 and IncHI2A (B), IncI1 (C), other Inc groups (including IncF, IncHI1, IncL/M, and IncQ1) (D), and no Inc detected (E). Below each AMR gene are the antimicrobials that the gene confers resistance to, and the number of plasmids in the long-read data set that the gene is located on. Antibiogram abbreviations: amoxicillin-clavulanic acid (AMC), ampicillin (AMP), azithromycin (AZM), ceftriaxone (CRO), cefoxitin (FOX), ciprofloxacin (CIP), chloramphenicol (CHL), gentamicin (GEN), nalidixic acid (NAL), streptomycin (STR), sulfisoxazole (SSS), tetracycline (TET), and trimethoprim-sulfamethoxazole (SXT).
In addition to Genr and Specr, the majority of closed plasmids encoded resistance to β-lactams (some conferring resistance to extended-spectrum cephalosporins), tetracycline, and other aminoglycosides, including kanamycin. Among the closed IncHI2 plasmids, there were three Genr genes [aac(3)-IId, aac(3)-IVa, and aac(6)-Ib-cr], two specr genes (aadA1 and aadA2), and two other genes that confer resistance to other aminoglycosides associated with this group. The ESBL gene blaCTX-M-14 and the mobile colistin resistance gene mcr-1 were both detected on an IncH12 plasmid in one human-source S. 4,[5]12:i:− isolate. Among the IncA/C2 plasmid group (n = 5), two Genr genes [aac(3)-IId and aac(3)-VIa], two Specr genes (aadA1 and aadA2), and two other aminoglycoside resistance genes were detected. Of the five IncA/C2 plasmids, one carried the ESBL blaCTX-M-14 (in S. 4,[5]12:i:−), and four carried the AmpC-type β-lactamase blaCMY-2 (in one S. Typhimurium, one S. 4,[5]12:i:−, and two S. Infantis). The IncI1 group (n = 5) carried the Genr genes aac(3)-IId (n = 1) and aac(3)-VIa (n = 4), as well as the Specr gene ant(3′′)-Ia (n = 4). AmpC-type β-lactamase blaCMY-2 was detected on one IncI1 plasmid from S. Typhimurium. The group without a detectable Inc group (n = 3) all shared the same Genr gene [aac(3)-Iva], Specr gene [ant(3′′)-Ia], and other aminoglycoside resistance genes. The ESBL blaCTX-M-65 was present on all three plasmids. In the “other” Inc group category (n = 8), a variety of Genr, Specr, and other resistance genes were detected, in this diverse plasmid group. Tetracycline resistance genes were detected in closed plasmids from all five Inc groups, with chloramphenicol resistance genes also detected in the IncHI2 group.


There is an urgent need to preserve the effectiveness of antimicrobials for humans and animals, and governments and agricultural sectors are working together to ensure responsible use of antimicrobial drugs (18). Here, we found that Genr Salmonella in human and chicken sources shared some similarities in terms of genomic backgrounds, resistance genes, and resistance plasmids.
Of the select eight Salmonella serovars from human source tested by CIPARS, the highest frequency of gentamicin resistance was found in Salmonella Heidelberg, 4,[5],12:i:−, Kentucky, Infantis, and Typhimurium. Among these serovars, gentamicin resistance increased in the period 2014 to 2017 compared to 2003 to 2013 in isolates from both human and chicken sources. Phylogenomic analyses revealed clusters of related isolates in some of these serovars. For S. Heidelberg, we identified closely related isolates from human and chicken sources that differed by fewer than 30 SNVs. A similar outcome was observed in S. Infantis, which had three clusters of isolates from human, animal, and retail sources, with some clusters differing by five or fewer SNVs. This suggests either potential transmission of Genr Salmonella between chicken and humans for S. Heidelberg and S. Infantis or circulation of the same strains in chickens and humans. For S. 4,[5],12:i:− and S. Typhimurium, there was one cluster each of closely related isolates from both human and chicken sources. Other than these two clusters, isolates of S. 4,[5],12:i:− and S. Typhimurium from human and chicken sources were generally not closely related, suggesting few instances of potential transmission. S. 4,[5],12:i:− (a monophasic variant of S. Typhimurium) has been associated with multiple outbreaks of salmonellosis due to contaminated pork (19, 20) and is associated with resistance to many antimicrobial classes (21). Our data are consistent with this, as over half of all isolates resistant to ≥6 antimicrobial classes were 4,[5],12:i:−. As expected, S. Kentucky isolates from human and chicken sources differed by approximately 20,000 SNVs. S. Kentucky is known to be polyphyletic, with ST198 causing infections in human and cattle and ST152 causing infection in poultry (22). S. Kentucky infection in humans may be the result of international travel or also due to the consumption of contaminated dairy products such as unpasteurized milk or cheese (23, 24).
A large proportion of isolates were multidrug resistant, with over 70% of all Genr Salmonella isolates displaying resistance to three or more antimicrobial classes, and over 60% of all human-source isolates displaying resistance to four or more classes of antimicrobials. Coresistance with ceftriaxone, ciprofloxacin, and colistin, which are classified by Health Canada as category 1 (very high importance to human medicine) antimicrobials, was observed as was coresistance to category II and III antimicrobials. Also of note were the seven isolates in which no Genr gene was detected in, even though they were phenotypically resistant. These isolates may represent opportunities to identify novel Genr genes or mutations in future studies through more in-depth genome analysis, as others have done previously (25).
Aminoglycoside-modifying enzymes (AMEs) are the most common mechanism of resistance to aminoglycosides within Enterobacterales (14), with the AAC class being the most common. In our study, aac(3)-VIa was the most frequent Genr gene identified in both human and chicken isolates. This gene was previously identified as a frequent cause of Genr in E. coli from broiler chickens from Quebec, Canada (17), suggesting that it commonly confers Genr in both Salmonella and E. coli in Canada. Besides gentamicin, some AMEs identified here also confer resistance to other aminoglycosides such as tobramycin and dibekacin (13). The vast majority of Lincor/Specr genes detected conferred resistance specifically to spectinomycin, which would therefore not confer resistance to the antimicrobial combination. These genes, including ant(3′′)-Ia and several aadA genes, all code for the enzyme ANT(3′′)-I. Seven human isolates carried lnuF, which confers resistance to lincomycin. Since the presence of a Genr gene was detected in approximately 90% of isolates that possessed a Specr gene, and vice versa, it appears that these two genes are strongly coselected, perhaps due to selective pressure from the use of lincomycin-spectinomycin on farms; however, it is unclear why so few Lincor genes were detected, while Specr genes were more abundant. It is possible that Lincor genes confer a fitness cost to the host Salmonella.
The presence of ESBLs conferring resistance to extended-spectrum cephalosporins on Genr plasmids is concerning, since this is an important treatment option for human infections caused by Salmonella and other Enterobacterales (26). Associations of aminoglycoside resistance genes and ESBLs in Enterobacterales in the Inc types identified here have been previously noted (2628). We found two colistin resistance genes, which is notable as colistin is a last-line drug used to treat infections caused by extensively resistant Gram-negative pathogens, including the Enterobacterales, Pseudomonas aeruginosa, and Acinetobacter baumannii (29). One plasmid harbored the rmtB gene encoding a 16S rRNA methyltransferase (RMT). The rmtB gene inhibits plazomicin, a next-generation aminoglycoside used to treat complicated urinary tract infections (UTIs) that are resistant to other aminoglycosides (30).
In conclusion, our findings support the potential transmission of Genr Salmonella between chicken and human sources, as isolates of S. Heidelberg and S. Infantis from both sources appeared to be closely related, and resistance genes and plasmids were similar between the two sources. The most commonly identified Genr and Specr genes were the same in both sources and were frequently linked on the same plasmids, which supports the hypothesis that Genr may be coselected by lincomycin-spectinomycin use on farms.


Isolate collection and susceptibility testing.

The Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS) uses a One-Health approach to monitor antimicrobial use and resistance in enteric bacteria isolated from human and agrifood sources across Canada. CIPARS carries out antimicrobial susceptibility testing (AST) on all Salmonella serovars collected from surveillance of chicken sources (clinical, manure, cecal) and retail chicken products. CIPARS also routinely carries out AST on five NTS serovars from human isolates (S. 4,[5],12:i:−, Enteritidis, Heidelberg, Newport, and Typhimurium) as well as other select serovars (S. Dublin, Infantis, and Kentucky) due to concerns regarding antimicrobial resistance. Further information on the sampling and testing methods used by CIPARS can be found in the annual reports (31). This study focused on Salmonella isolates that were resistant to gentamicin. CIPARS carried out antimicrobial susceptibility testing by broth microdilution with the Sensititre Complete Automated AST System using the CMV3AGNF panel in 2014 to 2015 and the CMV4AGNF panel in 2016 and 2017. Thirteen antimicrobials were tested in all years (amoxicillin-clavulanic acid, ampicillin, azithromycin, cefoxitin, ceftriaxone, chloramphenicol, ciprofloxacin, gentamicin, nalidixic acid, sulfisoxazole, streptomycin, sulfamethoxazole-trimethoprim, and tetracycline). MICs were interpreted according to breakpoints from the Clinical and Laboratory Standards Institute (32) for all drugs except azithromycin, for which we used an epidemiological cutoff of ≥32 μg/ml that is standardized with the U.S. National Antimicrobial Resistance Monitoring System (NARMS) program. Susceptible, intermediate, and resistant breakpoints for gentamicin were ≤4 μg/ml, 8 μg/ml, and ≥16 μg/ml, respectively. The isolates were categorized by isolation source as one of the following: animal (those from live and recently slaughtered broiler chickens collected from farms and abattoirs, and veterinary clinical samples), retail (those from chicken meat collected from stores), or human (samples submitted to provincial public health laboratories by hospital-based and private clinical laboratories). The total study population of Genr isolates collected from 2014 to 2017 (n = 247) included 188 isolates from humans and 59 from chicken sources (26 from animal and 33 from retail).

Whole-genome sequencing.

Short-read whole-genome sequencing (WGS) was performed on isolates collected from 2014 to 2017 that were resistant to gentamicin (n = 247). DNA was extracted using the DNeasy 96 blood and tissue kit (Qiagen). DNA libraries were prepared using Nextera XT. WGS was performed on the Nextseq platform (Illumina) using Nextseq 500/550 150 cycle kits to obtain a minimum coverage of ≥40× for all isolates. For long-read sequencing, a convenience sample of isolates was chosen (n = 29) that included the isolates with resistance to ≥6 classes of antimicrobials tested, with the remaining samples chosen to diversify the range of isolate sources, serovars, resistance profiles, and plasmid types. Twenty-five of these isolates were human-source isolates, and four isolates were from chicken. DNA extractions were carried out using the MasterPure Complete DNA & RNA purification kit (Lucigen, USA). Libraries were prepared using the Native Barcoding Expansion 1-12 kit (Oxford Nanopore Technologies), and sequencing was performed on the MinION platform (Oxford Nanopore Technologies).

Genomic analysis.

Phylogenomic trees were constructed for the five serovars found to be most frequently resistant to gentamicin in human isolates in this study. Phylogenomic analyses based on single nucleotide variants (SNVs) in the core genome were carried out with the SNVPhyl v1.0.1b (33) pipeline (minimum coverage, 15; minimum mean mapping quality, 30; SNV abundance ratio, 0.75; density filter, 2 or more SNVs per 20-base window). Genomes were assembled from short reads using SPAdes v3.11.1 with FLASH v1.2.11.3 (34), and resistance genes were identified with Staramr v0.6.0 (https://github.com/phac-nml/staramr; percent length overlap of BLAST hit for ResFinder database, 52). A subset of genomes were constructed from hybrid assembly of short reads and long reads using Unicycler v0.4.7 (35), and assemblies were annotated using Prokka v1.13 (36). Plasmids were visualized using GView v1.7 (37) (GView Server; https://server.gview.ca/) where pangenome analyses were conducted using BLASTn (parameters: expected value cutoff, 1 × 10−10; alignment length cutoff, 150; percent identity cutoff, 98). To quantify plasmid similarity, nucleotide sequences were aligned with BLASTn using Megablast to optimize for highly similar sequences.

Accession number(s).

Sequence read data for all 247 Salmonella isolates were submitted to the National Center for Biotechnology Information (NCBI) in BioProject accession no. PRJNA746107. BioSample identifiers (IDs) for all isolates are listed in Table S1 in the supplemental material.


We thank the National Microbiology Laboratory’s Genomics Core Facility and Bioinformatics Core Facility for support with whole-genome sequencing and bioinformatics. We also thank the technicians at the National Microbiology Laboratory (NML) Winnipeg, NML Guelph, and NML Saint-Hyacinthe laboratories for performing antimicrobial susceptibility testing.
This research was supported by a grant from the Canadian Institutes for Health Research (CFC-150770).
We declare that we have no conflicts of interest.

Supplemental Material

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Thomas MK, Murray R, Flockhart L, Pintar K, Pollari F, Fazil A, Nesbitt A, Marshall B. 2013. Estimates of the burden of foodborne illness in Canada for 30 specified pathogens and unspecified agents, circa 2006. Foodborne Pathog Dis 10:639–648.
Bopp CA, Fields PI, Nataro JP, Strockbine NA, Kaper JB. 2015. Escherichia, Shigella, and Salmonella, p 685–713. In Jorgensen JH, Pfaller MA, Carroll KC, Funke G, Landry ML, Richter SS, Warnock DW (ed), Manual of clinical microbiology, 11th ed, vol 1. ASM Press, Washington, DC.
Andino A, Hanning I. 2015. Salmonella enterica: survival, colonization, and virulence differences among serovars. Sci World J 2015:520179.
Crump JA, Sjölund-Karlsson M, Gordon MA, Parry CM. 2015. Epidemiology, clinical presentation, laboratory diagnosis, antimicrobial resistance, and antimicrobial management of invasive Salmonella infections. Clin Microbiol Rev 28:901–937.
Dougherty B, Finley R, Marshall B, Dumoulin D, Pavletic A, Dow J, Hluchy T, Asplin R, Stone J. 2020. An analysis of antibiotic prescribing practices for enteric bacterial infections within FoodNet Canada sentinel sites. J Antimicrob Chemother 75:1061–1067.
Krause KM, Serio AW, Kane TR, Connolly LE. 2016. Aminoglycosides: an overview. Cold Spring Harb Perspect Med 6:a027029.
Becker B, Cooper MA. 2013. Aminoglycoside antibiotics in the 21st century. ACS Chem Biol 8:105–115.
Ramirez MS, Tolmasky ME. 2010. Aminoglycoside modifying enzymes. Drug Resist Updat 13:151–171.
Health Canada. 2009. Categorization of antimicrobial drugs based on importance in human medicine. Health Canada, Ottawa, Ontario, Canada. https://www.canada.ca/en/health-canada/services/drugs-health-products/veterinary-drugs/antimicrobial-resistance/categorization-antimicrobial-drugs-based-importance-human-medicine.html. Accessed 29 December 2020.
van Duijkeren E, Schwarz C, Bouchard D, Catry B, Pomba C, Baptiste KE, Moreno MA, Rantala M, Ružauskas M, Sanders P, Teale C, Wester AL, Ignate K, Kunsagi Z, Jukes H. 2019. The use of aminoglycosides in animals within the EU: development of resistance in animals and possible impact on human and animal health: a review. J Antimicrob Chemother 74:2480–2496.
Vakulenko SB, Mobashery S. 2003. Versatility of aminoglycosides and prospects for their future. Clin Microbiol Rev 16:430–450.
Fuchs A, Bielicki J, Mathur S, Sharland M, Van Den Anker JN. 2018. Reviewing the WHO guidelines for antibiotic use for sepsis in neonates and children. Paediatr Int Child Health 38:S3–S15.
Shaw KJ, Rather PN, Hare RS, Miller GH. 1993. Molecular genetics of aminoglycoside resistance genes and familial relationships of the aminoglycoside-modifying enzymes. Microbiol Rev 57:138–163.
Garneau-Tsodikova S, Labby KJ. 2016. Mechanisms of resistance to aminoglycoside antibiotics: overview and perspectives. Medchemcomm 7:11–27.
Public Health Agency of Canada. 2018. Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS) 2016 Annual Report. Public Health Agency of Canada, Ottawa, Ontario, Canada.
Agunos A, Gow SP, Léger DF, Carson CA, Deckert AE, Bosman AL, Loest D, Irwin RJ, Reid-Smith RJ. 2019. Antimicrobial use and antimicrobial resistance indicators—integration of farm-level surveillance data from broiler chickens and turkeys in British Columbia. Front Vet Sci 6:131.
Chalmers G, Cormier AC, Nadeau M, Côté G, Reid-Smith RJ, Boerlin P. 2017. Determinants of virulence and of resistance to ceftiofur, gentamicin, and spectinomycin in clinical Escherichia coli from broiler chickens in Québec, Canada. Vet Microbiol 203:149–157.
Expert Panel on the Potential Socio-Economic Impacts of Antimicrobial Resistance in Canada. 2019. When antibiotics fail. Council of Canadian Academies, Ottawa, Ontario, Canada.
Arruda BL, Burrough ER, Schwartz KJ. 2019. Salmonella enterica I 4,[5],12:i:- associated with lesions typical of swine enteric salmonellosis. Emerg Infect Dis 25:1377–1379.
Ido N, Lee K, Iwabuchi K, Izumiya H, Uchida I, Kusumoto M, Iwata T, Ohnishi M, Akiba M. 2014. Characteristics of Salmonella enterica serovar 4,[5],12:i:- as a monophasic variant of serovar Typhimurium. PLoS One 9:e104380.
Naberhaus SA, Krull AC, Bradner LK, Harmon KM, Arruda P, Arruda BL, Sahin O, Burrough ER, Schwartz KJ, Kreuder AJ. 2019. Emergence of Salmonella enterica serovar 4,[5],12:i:- as the primary serovar identified from swine clinical samples and development of a multiplex real-time PCR for improved Salmonella serovar-level identification. J Vet Diagn Invest 31:818–827.
Le Hello S, Hendriksen RS, Doublet B, Fisher I, Nielsen EM, Whichard JM, Bouchrif B, Fashae K, Granier SA, Jourdan-Da Silva N, Cloeckaert A, Threlfall EJ, Angulo FJ, Aarestrup FM, Wain J, Weill F-X. 2011. International spread of an epidemic population of Salmonella enterica serotype Kentucky ST198 resistant to ciprofloxacin. J Infect Dis 204:675–684.
Van Kessel JAS, Karns JS, Lombard JE, Kopral CA. 2011. Prevalence of Salmonella enterica, Listeria monocytogenes, and Escherichia coli virulence factors in bulk tank milk and in-line filters from U.S. dairies. J Food Prot 74:759–768.
Van Kessel JAS, Karns JS, Wolfgang DR, Hovingh E, Schukken YH. 2012. Dynamics of Salmonella serotype shifts in an endemically infected dairy herd. Foodborne Pathog Dis 9:319–324.
Kim H-SL, Rodriguez RD, Morris SK, Zhao S, Donato JJ. 2020. Identification of a novel plasmid-borne gentamicin resistance gene in nontyphoidal Salmonella isolated from retail turkey. Antimicrob Agents Chemother 64:e00867-20.
Rawat D, Nair D. 2010. Extended-spectrum β-lactamases in gram negative bacteria. J Glob Infect Dis 2:263–274.
Exner M, Bhattacharya S, Christiansen B, Gebel J, Goroncy-Bermes P, Hartemann P, Heeg P, Ilschner C, Kramer A, Larson E, Merkens W, Mielke M, Oltmanns P, Ross B, Rotter M, Schmithausen RM, Sonntag H-G, Trautmann M. 2017. Antibiotic resistance: what is so special about multidrug-resistant Gram-negative bacteria? GMS Hyg Infect Control 12:Doc05.
Rozwandowicz M, Brouwer MSM, Fischer J, Wagenaar JA, Gonzalez-Zorn B, Guerra B, Mevius DJ, Hordijk J. 2018. Plasmids carrying antimicrobial resistance genes in Enterobacteriaceae. J Antimicrob Chemother 73:1121–1137.
Shaikh S, Fatima J, Shakil S, Rizvi SMD, Kamal MA. 2015. Antibiotic resistance and extended spectrum beta-lactamases: types, epidemiology and treatment. Saudi J Biol Sci 22:90–101.
Böhm M-E, Razavi M, Marathe NP, Flach C-F, Larsson DGJ. 2020. Discovery of a novel integron-borne aminoglycoside resistance gene present in clinical pathogens by screening environmental bacterial communities. Microbiome 8:41.
Public Health Agency of Canada. 2018. Canadian Integrated Program for Antimicrobial Resistance Surveillance (CIPARS) 2018 Design and Methods. Public Health Agency of Canada, Guelph, Ontario, Canada. https://www.canada.ca/content/dam/phac-aspc/documents/services/surveillance/canadian-integrated-program-antimicrobial-resistance-surveillance-cipars/cipars-reports/2018-annual-report-design-methods/2018-annual-report-design-methods.pdf. Accessed 30 December 2020.
Clinical and Laboratory Standards Institute. 2017. Performance standards for antimicrobial susceptibility testing. 27th edition. CLSI supplement M100. Clinical and Laboratory Standards Institute, Wayne, PA.
Petkau A, Mabon P, Sieffert C, Knox NC, Cabral J, Iskander M, Iskander M, Weedmark K, Zaheer R, Katz LS, Nadon C, Reimer A, Taboada E, Beiko RG, Hsiao W, Brinkman F, Graham M, Van Domselaar G. 2017. SNVPhyl: a single nucleotide variant phylogenomics pipeline for microbial genomic epidemiology. Microb Genom 3:e000116.
Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, Lesin VM, Nikolenko SI, Pham S, Prjibelski AD, Pyshkin AV, Sirotkin AV, Vyahhi N, Tesler G, Alekseyev MA, Pevzner PA. 2012. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol 19:455–477.
Wick RR, Judd LM, Gorrie CL, Holt KE. 2017. Unicycler: resolving bacterial genome assemblies from short and long sequencing reads. PLoS Comput Biol 13:e1005595.
Seemann T. 2014. Prokka: rapid prokaryotic genome annotation. Bioinformatics 30:2068–2069.
Petkau A, Stuart-Edwards M, Stothard P, van Domselaar G. 2010. Interactive microbial genome visualization with GView. Bioinformatics 26:3125–3126.

Information & Contributors


Published In

cover image Antimicrobial Agents and Chemotherapy
Antimicrobial Agents and Chemotherapy
Volume 65Number 1217 November 2021
eLocator: 10.1128/aac.00966-21


Received: 19 May 2021
Returned for modification: 26 June 2021
Accepted: 18 August 2021
Accepted manuscript posted online: 27 September 2021
Published online: 17 November 2021


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  1. aminoglycosides
  2. antimicrobial resistance
  3. genomics
  4. gentamicin
  5. poultry
  6. whole-genome sequencing



Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Manitoba, Canada
National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
E. Jane Parmley
Centre for Food-borne, Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, Ontario, Canada
Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, Ontario, Canada
Brent P. Avery
Centre for Food-borne, Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, Ontario, Canada
Rebecca J. Irwin
Centre for Food-borne, Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, Ontario, Canada
Richard J. Reid-Smith
Centre for Food-borne, Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, Ontario, Canada
Anne E. Deckert
Centre for Food-borne, Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, Ontario, Canada
Rita L. Finley
Centre for Food-borne, Environmental and Zoonotic Infectious Diseases, Public Health Agency of Canada, Guelph, Ontario, Canada
Danielle Daignault
National Microbiology Laboratory, Public Health Agency of Canada, St. Hyacinthe, Quebec, Canada
David C. Alexander
Cadham Provincial Laboratory, Winnipeg, Manitoba, Canada
Vanessa Allen
Public Health Ontario Laboratories, Toronto, Ontario, Canada
Sameh El Bailey
Horizon Health Network, Saint John, New Brunswick, Canada
Sadjia Bekal
Laboratoire de Santé Publique du Québec, Sainte-Anne-de-Bellevue, Quebec, Canada
Alberta Precision Laboratories-Provincial Laboratory for Public Health, Edmonton, Alberta, Canada
Department of Laboratory Medicine and Pathology, University of Alberta, Edmonton, Alberta, Canada
Greg J. German
Queen Elizabeth Hospital, Charlottetown, Prince Edward Island, Canada
David Haldane
Queen Elizabeth II Health Sciences Centre, Halifax, Nova Scotia, Canada
Linda Hoang
British Columbia Centre for Disease Control, Vancouver, British Columbia, Canada
Jessica Minion
Roy Romanow Provincial Laboratory, Regina, Saskatchewan, Canada
George Zahariadis
Newfoundland and Labrador Public Health and Microbiology Laboratory, St. John’s, Newfoundland and Labrador, Canada
Michael R. Mulvey
Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Manitoba, Canada
National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada
Department of Medical Microbiology and Infectious Diseases, University of Manitoba, Winnipeg, Manitoba, Canada
National Microbiology Laboratory, Public Health Agency of Canada, Winnipeg, Manitoba, Canada

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